The present invention generally relates to epilepsy therapy and more specifically to an implantable seizure detection and warning apparatus for epileptic patients.
Epilepsy is a condition characterized by recurrent seizures of various types associated with disturbances of consciousness. The incidence of epilepsy has been estimated at one of every two hundred to three hundred of the population. In the United States, the number of cases exceeds two hundred and fifty thousand individuals.
A variety of seizure types have been recognized including grand mal seizures, petit mal seizures, psychomotor seizures, Jacksonian seizures and focal seizures. A seizure may or may not follow warning symptoms detectable to the patient. Major attacks begin with a sudden loss of consciousness. As the attack continues to develop, all voluntary muscles go into severe spasm, breathing ceases, the patient's skin turns blue, and life seems almost at an end. The patient then suddenly becomes totally relaxed and muscle spasms are replaced by jerking or clonic uncontrolled motions of increasing strength. Finally, the spasms cease altogether and consciousness gradually returns.
A seizure may appear to occur spontaneously, without external stimuli, although in many patients a stimulus such as flashing lights, repetitive sounds or stressful situations are easily identified as the trigger of the seizure. While seizures often occur during sleep, a seizure during waking hours may cause the patient to injure himself when consciousness is suddenly lost. The danger posed to the epileptic patient and others is obvious. He may fall and strike his head, fall into moving machinery or lose control of an automobile.
The recent decades have seen a real increase in the inclusion of epileptic patients in family life, social activities and business. Medical treatment can control seizures in about seventy-five percent of epileptic patients, but each patient must minimize exposure to many inherently dangerous situations commonly encountered in a modern industrial society. Obtaining a driver's license for a patient remains a difficulty, and the knowledge of the possibility of unexpected attacks causes chronic anxiety in many patients.
Internally, the onset of a seizure is reflected in a marked departure of brain potential from the normal form. The characteristic feature of the normal adult electroencephalogram (EEG) is an Alpha rhythm in a frequency range of eight to twelve hertz at a potential measured in the microvolt range. An example of a normal adult waking state EEG tracing is illustrated in FIG. 1.
Higher voltage processes of unique form are intimately linked with seizures and are called paroxysmal. A typical paroxysmal waveform is illustrated in FIG. 2. These waves may arise in a single focal area of the brain and spread gradually to other areas, or instead rapidly involve all cerebral areas, and the type of waveform exhibited will also vary from patient to patient. However, in any one patient it is highly likely that the EEG waveform and propagation pattern at seizure onset will repeat the pattern of prior seizures. While other disease states such as migraine, narcolepsy and vertigo involve high voltage EEG patterns, so that the pattern alone is not uniquely diagnostic of epilepsy, the EEG spikes of epilepsy are useful documentation of the disease during seizures. The high voltage waveform is infrequent and less numerous in the interictal period of epileptic patients and is then a particularly important diagnostic tool. A changing frequency of transient spikes may be related to changes in the severity of the disease, and has been used to assess the effectiveness of drug therapy.
The analysis of EEG sharp transients according to frequency and configuration continues to hold promise as the method for evaluating epileptic patients in response to drug control of epilepsy.
Standard EEG procedures utilize electrodes applied to the scalp and coupled to systems employed to measure and record the electropotential changes associated with normal and abnormal cerebral activity. The patient is typically connected directly by wires to the system, and must lie motionless during a period of approximately twenty minutes to complete the study. This technique incorporates some substantial limitations. The very short time of study of the patient may not include abnormal EEG activity. The patient is isolated from normal daily activity which may include seizure stimuli. Furthermore, any type of muscle activity, including movements of the eye, produces strong aberrations in the EEG tracing. Moreover, observer analysis and interpretation of EEG tracings remains more an art than a science with the possibility for wide disagreement between observers of an EEG.
Radiotelemetry systems designed to monitor the EEG potentials remotely were developed late in the 1940's. Electrodes applied to the scalp were coupled to a portable transmitter unit worn by the patient. The radio signals were then received by a remote receiver and converted to a tracing displayed on a oscilloscope or paper. Such developments offered an opportunity to monitor epileptic patients in something akin to a daily routine over an extended period of time. A therapy plan could then include a quantitative correlation of seizures and EEG activity in evaluating the efficacy of anti-epileptic drugs.
Initially, EEG telemetry units of practical size and mass were of low power, restricting the monitored patient to a small area within range of the telemetry receiver. However, advancements in solid state electronics technology gave rise to more powerful transmitters and by 1973, nine manufacturers were offering EEG telemetry equipment. Two channel, three channel and sixteen channel transmitters were made available for simultaneous monitoring of separate areas of the brain. These systems experienced external interference on AM channels by sources such as motors and fluorescent lights and, on FM channels, by commercial FM stations.
Other developments have improved the usefulness of portable EEG monitoring systems. A portable cassette EEG recorder was demonstrated in 1975, and has been improved to include four channel recording capability. While the cassette recorder adds somewhat to the burden carried by the patient and prohibits correlation with patient activities, it does allow capture of data away from receivers in the patient's normal environment and without interference. The development of economical video recording systems have allowed simultaneous EEG and video monitoring to correlate external patient symptoms with EEG changes, although this system also involves restraining the patient to an area close by a video camera. Band pass filters have been successfully developed to minimize interference from muscle potentials. An induction-powered, implanted EEG transmitter has also been introduced.
Development of EEG analysis systems has lagged behind the advances in EEG data capture and transmission systems. The techniques used to analyze EEG data from epileptic patients generally require the use of a digital computer. The size, mass and power requirements of such a computer have heretofore implied a stationary computer and a patient within transmission distance of the computer. Despite these inadequacies, computer analysis of EEG data is now entering clinical use, and remains an area of intense study.
Analysis techniques under scrutiny include matched filtering, also known as "template matching", time-averaged running correlation coefficients analysis, and fast Fourier analysis of component frequencies. EEG sharp transient detection and quantification has received great attention because transients are one of the more important features in the EEG tracings of epileptic patients. A representative system is one which detects brain waves with a second derivative exceeding the average second derivative of the preceding wave by more than a specified threshold mount. This system can act as a smart sensor of sharp transients, and notify a diagnostician to examine the tracings more closely. Template matching techniques can detect a specific waveform quite dependably, but departures from the waveform template are not detected at all. Computation of a running correlation coefficient between two EEG channels has the potential of signalling a change in the EEG, provided that only one channel changes.
The development of the fast Fourier transform algorithm for digital spectral analysis offers accurate and flexible recognition of various waveforms. However, the use of Fourier analysis has heretofore been limited, like the aforementioned analysis techniques, to relatively powerful and stationary computer systems.